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Webinars

Woman sitting working on her computer

Tools from the Couch is an opportunity to share the diverse expertise that exists in the department and broader community on different computational (or otherwise!) tools that we use for our research. This is an extension of but includes the Data Science Groups from past terms. Weekly sessions on different topics are held every Thursday at 1:00pm EDT on zoom.

Please register your interest in the series here.

Please email Mark Richardson for more information.

Upcoming Sessions

Thursday, June 4th, 2020
Title: Intro to Tools for Machine Learning
Lead: Connor Stone
Overview: I will begin with a basic introduction to optimization using scipy minimize. Hopefully this session will help you take full advantage of this function when fitting models to data (machine learning or otherwise). I will also use this as an opportunity to introduce the concept of Regularization, which is a machine learning concept at the core of the success of many widely used algorithms like Neural Networks. Note, it is very common to come across functions with many local minima, so I will show how by using many minimized “walkers” it is possible to optimize a notoriously challenging function: “The Rastrigin”. I will then dive into sci-kit learn, and keras (and possibly pytorch, although it will depend on time and I would appreciate anyone with practical experience with pytorch to join in and share).

Thursday, June 11th, 2020: Directly Editing Vector Image Files – Zac Kenny

Thursday, June 18th, 2020: Discussion of Bayes’ Theorem and Statistics

Thursday, June 25th, 2020: Version Control: Git, Gitlab, Github, and Bitbucket – Mark Richardson

Thursday, July 2nd, 2020: Group Discussion of Queen’s High Performance Computing Resources

Thursday, July 9th, 2020: Parallel Computing: OpenMP and MPI – Mark Richardson

Thursday, July 16th, 2020: Group Discussion of where we learned to code.

Thursday, July 23rd, 2020: Markov Chain Monte Carlo (MCMC) Methods

Thursday, July 30th, 2020: Taking advantage of your graphic card: GPU Programming.

 

Previous Sessions

Thursday, May 28th, 2020
Discussion Topic: Group Discussion of Neural Networks and Machine Learning
Lead: Mark Richardson
Overview: As problems continue to require more data to solve, analysis of this data has become time-intensive. As a result, machine learning, the ability for a computer program to learn features of the dataset to expedite the analysis process, has become essential. From digitizing text, to classifying supernovae, and everything in between machine learning will play a huge part of the future of science. For this discussion session we will start a conversation about machine learning, both supervised and unsupervised, and then discuss neural networks in some detail. The format will be a discussion, where people can speak to their own experience implementing machine learning tools. Next week we will dive into some of the tools that exist and let people try them out at home. For this discussion, I encourage you to reflect on how you’ve used machine learning in your research etc. I also recommend the 3blue1brown series on neural networks: https://www.3blue1brown.com/neural-networks.

Click here for video and slides from the session.

Thursday, May 21st, 2020: After a two-week hiatus for new summer student orientation, we will be running a session on Overleaf and LaTeX.

Date: Thursday, May 21st, 1:00 PM EDT
Title: Overleaf and LaTeX
Speaker: Mark Richardson
Overview: This Thursday I will be doing a session on Overleaf and LaTeX. LaTeX is a powerful (if not occasionally annoying) tool for type-setting your scientific writing. This is the most common method that all physicists write their articles for publication. Overleaf is a cloud-based LaTeX server where you can host you latex files and relevant figures and bibliographies. You can also share with collaborators and work on your paper together in real-time. If you are unfamiliar with Overleaf or LaTeX, I recommend you join in to the session.
Registration: You can register here for the sessions as a whole, or email Mark Richardson directly (Mark.Richardson@queensu.ca). I will only send out Zoom details to those that register.

Thursday, May 7th, 2020: Instead of our usual session, we encourage people to join the C++ session being covered by the Queen’s New Student Particle Astrophysics Workshop (email Ben Tam for more information).

Thursday, Apr 30th, 2020: 1:00 – 2:30pm EDT (90 minutes)

An introduction to Matplotlib: Making publication-quality plots

Background: Matplotlib is a plotting library for python, used by many researchers today for generating publication-purpose figures. In this session, we will cover an introduction to Matplotlib, as well as methods for improving the look and feel of your plots.

Presenter: Simran Nerval is a physics master’s student at Queen’s University and researcher at the Arthur B. McDonald Canadian Astroparticle Physics Research Institute. She studies gravitational wave production during the expansion of the early universe. Before coming here, she did her undergraduate degree at the University of Toronto in physics and astronomy where she was a part of the Dunlap Institute for Astronomy and Astrophysics. While she was there, she was a part of the LiteBIRD collaboration and worked with the Canadian Space Agency to figure out how well the LiteBIRD satellite with be able to determine what occurred during the earliest moments of the universe. Alongside her research, she spends time doing a variety of science outreach for events ranging from classroom visits with Let’s Talk Science to Astronomy on tap.

Materials: A pre-made jupyter notebook is available here.

Prerequisites:

  • Python 3, with numpy, matplotlib
  • Jupyter notebook
  • Ideal: Latex font installed
  • Alternative: Access to online Jupyter client, such as syzergy: https://queensu.syzygy.ca/

Thursday, Apr 23rd, 2020: 1:30 – 2:30pm EDT (60 minutes)

An introduction to Jupyter Notebooks and Python 3

Background: Jupyter Notebook is a platform for keeping a research diary as you work through your analysis with embedded python. This session will introduce the Jupyter platform and then cover an introduction to Python3, the dominant language for scripting and analysis today.

Presenter: Mark Richardson is the Education and Outreach Officer for the McDonald Institute. He held postdocs at the American Museum of Natural History in 2017-2018, and Oxford University from 2014-2017, and completed his PhD in modeling Galaxy Formation and Evolution at Arizona State University in 2014.

Materials: A pre-made jupyter notebook is available here.

Prerequisites:

  • Python 3, preferably with numpy, matplotlib
  • Jupyter notebook
  • Alternative: Access to online Jupyter client, such as syzergy: https://queensu.syzygy.ca/